1. Field of the Invention
This invention relates to the field of pricing. In particular, the invention relates to methods and apparatus for automatically adjusting pricing on items in an electronic commerce environment.
2. Description of the Related Art
Electronic commerce sites enable business to sell products and services to consumers and other businesses. FIG. 1 broadly illustrates the basic configuration used by electronic commerce vendors. A web server 100 is coupled to a database 102 that includes pricing information for products, e.g. the product 105. When a client, not shown in FIG. 1, requests a web page, e.g. the web page 104, over a network such as the Internet, the web server 100 generates the web page 104. The web page 104 may include a reference to the product 105, e.g. a textual description, a picture, and/or some other reference, as well as a price 106. The dashed arrows in FIG. 1 illustrate that the web page 104 is generated from the web server 100, e.g. for the manual elements of the web page 104, and the database 102, e.g. for dynamic information such as product information and pricing. Logs such as the logs 110 can be maintained by the web server 100 to monitor usage of the sites hosted by the web server 100. Additionally, other servers may be used by the vendor to support the electronic commerce site, e.g. application servers, customer relationship management (CRM) systems, and/or other systems.
For a particular product, e.g. a book, a compact disc, a plane ticket, a grocery item, etc., the pricing displayed is typically controlled by one or more product merchandisers. These merchandisers are people with product area specific qualitative knowledge. The merchandisers set prices for items falling within their categories of pricing expertise in conjunction with other business policies.
For example, in the clothing business, there may be a product merchandiser who specializes in women's handbags and another in women's shoes. In order to set the price for an item, the merchandiser will qualitatively evaluate the market and the good considering factors such as: the good itself, the brand strength, market conditions, business goals, seasons, past sales, etc. Looked at from a microeconomics standpoint, the merchandiser is guessing the shape of the demand curve. And therefore, guessing the optimal price. This pricing approach will be referred to as manual pricing.
FIG. 2 illustrates the impact that traditional, manual, pricing methodologies have as demand changes over time. The graph 200 shows the passage of time on the X-axis. The relative demand of a given product over time is represented by the dotted curve 202. The pricing under a manual pricing model is shown as the stepped solid line 204. Notice that while the manual price 204 can be adjusted, e.g. by a merchandiser, based on current market conditions, it only roughly tracks the demand, and therefore the optimal price.
Thus, at times when demand is peaking—and therefore higher prices could be charged—the manual price does not respond. Similarly, as demand dips sharply, the manual price does not respond either. Further, because of the need for manual intervention to adjust the manual price 204, the price may not be adjusted frequently enough to capture either large or small market trends.
As the number of items that need to be priced grows and the business rules for determining prices become more complex, the manual pricing model becomes extremely untenable.
Some automated pricing models have been developed that facilitate the adjustment of manual prices based on predictive estimates of demand. These models typically emulate the assumptions that a merchandiser would use and can automate the process of adjusting prices in response to the inputs to the predictive models. The results do not look significantly different from FIG. 2.
In order to address the problems of manual pricing, some electronic commerce providers have adopted auction and/or reverse auction models, as well as variants. Priceline.com with its “Name your price”-style services for airline tickets, groceries, and gasoline, is a notable example of a variant of a reverse auction. However, using a reverse auction comes at the cost of convenience to the transaction, and in Priceline.com's case, consumer choice.
Accordingly, what is needed is a pricing model that allows sellers to automatically adjust the prices of products, and services, for sale in non-negotiated and non-auction settings to provide efficient pricing for both buyers and sellers. Furthermore, an approach for determining the lifetime value of a customer should be provided to allow the vendor to set prices that balance long term gains, e.g. customer repeat business, versus short term gains.